Regression Type Estimators Using Multiple Auxiliary Information

Mukerjee, Rahul; Rao, T. J.; Vijayan, K.

doi:10.1111/j.1467-842x.1987.tb00742.x

Cited by 39 publications

(31 citation statements)

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“…Few authors studied the M-PhS, specifically they proposed different estimators where the auxiliary information is used in different ways. See for instance Mukerjee et al (1987) and Ahmed (2003). Mukerjee et al (1987) mainly consider the 3-PhS scheme.They do not suggest the best estimator, even if they give an optimum estimator in a linear class.…”

Section: Introductionmentioning

confidence: 97%

“…See for instance Mukerjee et al (1987) and Ahmed (2003). Mukerjee et al (1987) mainly consider the 3-PhS scheme.They do not suggest the best estimator, even if they give an optimum estimator in a linear class. Ahmed (2003) proposes a parametric class.…”

Section: Introductionmentioning

confidence: 97%

“…Both Mukerjee et al (1987) and Ahmed (2003) made some cost considerations. This paper develops further the results given in Diana et al (2004) to cope with a cost constraint.…”

Section: Introductionmentioning

confidence: 99%

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Multi-phase sampling under cost constraints

Diana

Tommasi

Preo

2007

Stat. Meth. & Appl.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

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Multi-phase sampling under cost constraints

Diana

Tommasi

Preo

2007

Stat. Meth. & Appl.

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“…There is a variety of literature available in this regard for example, Kiregyera (1984), Mukerjee et al (1987), Singh (2001), Singh et al (2004), Kadilar and Cingi (2005), Joarder (2009), (2011) and Omar and Joarder (2011). This idea of using information on some additional characteristic(s) (for example, auxiliary characteristic(s)) which are associated with the main quality characteristic of interest has also been used in quality control literature.…”

Section: Introductionmentioning

confidence: 99%

On enhanced control charting for process monitoring

Riaz¹

2013

Int. J. Phys. Sci.

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The information on auxiliary characteristics helps significantly in increasing the efficiency of control charts for detecting shifts in process parameters. In this study we proposed Shewhart type control charts, namely the r A chart, the (1984) and Wade and Woodall (1993). It has been observed that the proposed charts perform superior, in terms of discriminatory power, as compared to the above mentioned counterparts, depending upon the correlation structure among the auxiliary characteristics and the quality characteristic of interest. The said superiority zone of the correlation structures, favoring the proposed charts, needs to be identified very carefully to apply it in a given situation.

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“…Most of the estimators differ in the sense of availability of different auxiliary variables and number of phases considered (Srivastava and Jhajj, 1981). In addition, a large deal of work has been done in suggesting regression and ratio type estimators, regression in regression, regression in ratio and ratio in regression estimators (Kiregyera, 1984;Mukerjee et al, 1987;Ahmed, 1998;Senapati and Sahoo, 2006). Similarly, there has been significant theoretical work on transform auxiliary variables (Mohanty and Sahoo, 1995;Singh, 2001).…”

Section: Introductionmentioning

confidence: 99%

A Class of Regression-Cum-Ratio Estimators in Two-Phase Sampling for Utilizing Information From High Resolution Satellite Data

Handique

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. Continuous satellite data with large area coverage provide scope for deriving population values of the auxiliary variables, which can effectively be used for estimating the population parameters of the variable of interest. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in two-phase sampling design and suggest an appropriate estimator that will be of broad interest and applications. A new class of regression-cumratio estimators has been proposed for two-phase sampling using information on two auxiliary variables derived from high resolution satellite data. The bias and the mean square error (MSE) of the proposed estimators have been obtained up to first order approximation. Efficiency comparison of the proposed estimators has been made with some traditional estimators. The proposed estimator is found to be more efficient than the usual regression and ratio estimators. Numerical illustration has been carried out to examine the efficiency of the estimator in case of forest timber volume estimation utilizing tree crown diameter and tree height as auxiliary variables. It is shown that these estimators can be employed in a variety of conditions where there is strong correlation of satellite derived information with sample based ground measurements and when the cost of ground measurements is relatively high.

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Regression Type Estimators Using Multiple Auxiliary Information

Cited by 39 publications

References 2 publications

Multi-phase sampling under cost constraints

Multi-phase sampling under cost constraints

On enhanced control charting for process monitoring

A Class of Regression-Cum-Ratio Estimators in Two-Phase Sampling for Utilizing Information From High Resolution Satellite Data

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